Comp/Phys/Mtsc 715 Lecture 3: Visualization Stages, Sensory vs. - PDF document

1/15/2014 Comp/Phys/Mtsc 715 Lecture 3: Visualization Stages, Sensory vs. Arbitrary symbols, Data Characteristics, Visualization Goals, Props Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 1 CH C/P/M 715, Taylor SP11 Example Videos • Dam breaking simulation • Multi-data-set isosurface similarity • Tumor access safety rays Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 2 CH C/P/M 715, Taylor SP11 Administrative • Office Hours: Sitterson 258 – Mondays 10-11 – Thursdays 9-10 • Homework – Wordpress site up and running – Some users registered – Upload your posts (private) by next Thursday! – Comment on posts by others by following Monday Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 3 CH C/P/M 715, Taylor SP11 1

1/15/2014 Foundation for a Science of Data Visualization • What are the advantages of visualization? Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 4 CH C/P/M 715, Taylor SP11 Visualization Stages • Collect the data (lab work or simulation) • Transform the data – into a format readable by the visualization software – into the form most likely to reveal information (Rspace) • Visualization algorithms run on graphics hardware or software renderer • Human views and interacts with the visualization (changing parameters, techniques, view direction) • Preferably: User studies to evaluate effectiveness Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 5 CH C/P/M 715, Taylor SP11 Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 6 CH C/P/M 715, Taylor SP11 2

1/15/2014 Sensory vs. Arbitrary Symbols • Sensory: You can see and understand without training. – Match the way our brains are wired – Object shape, color, texture • Arbitrary: Must be learned – Having no perceptual basis – The word “dog” • “perro”, “hund”, “chien”, “cane”, “cão”, “ 犬 ”, “ 개 ”, “ 狗 ” Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 7 CH C/P/M 715, Taylor SP11 Properties of Sensory Reps. • Can be understood without training • Resistant to instructional bias • Is processed very quickly, and in parallel • Is valid across cultures • Danger: Poor mappings can be misunderstood, even in the presence of instruction, quickly and without effort. Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 8 CH C/P/M 715, Taylor SP11 Properties of Arbitrary Reps. • Formally powerful • Capable of rapid change • May already be learned (summation notation) • Dangers: – Can be hard to learn (alphabet) – Can be easy to forget – Can vary with culture and application (different disciplines use different symbols for the same concept and the same symbol for different concepts): • i = sqrt(-1), i = current Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 9 CH C/P/M 715, Taylor SP11 3

1/15/2014 Two-Stage Model of Perceptual Processing Attentive Preattentive Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 10 CH C/P/M 715, Taylor SP11 Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 11 CH C/P/M 715, Taylor SP11 What is a Good Visualization? • Understanding means making a model that captures the essence of a system • A model is an abstraction with the important things in and the unimportant out • Different visualizations provide different levels of detail, show and hide different things; so support different abstractions • Good visualizations are those that are useful to aid understanding, not just realistic representations (what color is a carbon atom?) • Good visualizations map the important parts of the task onto techniques that show the relevant characteristics best Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 12 CH C/P/M 715, Taylor SP11 4

1/15/2014 Data Characteristics and Visualization Goals • Why classify data and visualization goals? – No known “silver bullet” technique – Helps select which technique(s) to try – Helps predict other uses for good techniques – Some tools only work with some formats (This section draws heavily on sources outside the Ware book) Print this lecture for reference (homeworks)! Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 13 CH C/P/M 715, Taylor SP11 Data Characteristics • Dimensionality • Category of each value/field • Structure of the sampling • Other data characteristics Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 14 CH C/P/M 715, Taylor SP11 Dimensionality • Of each data field (0=point, 1=line, 2=surface, 3=volume, …) • Of the space the fields are embedded in (2D or 3D) + time (some call 4D) • Of the data type in each field Two 2D scalar fields – (scalar, vector, tensor) in 2D (drawn in 3D) • Of the space used to visualize the data 2D vec/tensor fields 2D isosurfaces of Embedded in 3D 3D scalar field in 3D 3D vector field in 3D Drawn in 2D Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 15 CH C/P/M 715, Taylor SP11 5

1/15/2014 Category of each Scalar Field • Nominal: names without ordering – Continents: Africa, America, Asia, Australia, Europe. • Ordinal: “Less than” relationship holds – Rental cars: Economy, Compact, Mid-sized, Full-sized. • Interval: Relative measurements, no absolute zero – Height of AFM scan or location • Ratio: Absolute zero (can say “twice as much as”) – Account balance, Height above sea level, not “height” Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 16 CH C/P/M 715, Taylor SP11 Structure of the Sampling Grid • Structured • Structured – Square/Cube – Square/Cube – Rectilinear – Rectilinear – Curvilinear – Curvilinear • Unstructured • Unstructured – Tetrahedral – Tetrahedral – Cloud of points – Cloud of points Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 17 CH C/P/M 715, Taylor SP11 Other Data Characteristics • Continuous vs. Discrete – Sampling of the field – Values within each sample • Rapid spatial/temporal changes in the data • Missing values? – Interpolate? – Show explicitly? • Special values? – Of particular interest to visualize – Zero for some ratio scales (height above sea level) Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 18 CH C/P/M 715, Taylor SP11 6

1/15/2014 Data Characteristics: Example Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 19 CH C/P/M 715, Taylor SP11 Data Characteristics: Example Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 20 CH C/P/M 715, Taylor SP11 Visualization Problems vs. Data Types Medical Scientific Information n D 2D 3D 2D Scalar Square 3D Scalar Rectilinear Structured Unstructured Scalar Vector Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 21 CH C/P/M 715, Taylor SP11 7

1/15/2014 Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 22 CH C/P/M 715, Taylor SP11 Goal-Based Visualization Design • High-level goals / middle-level tasks / atomic actions • Determine task(s) before determining representations!!! – tasks often determined informally or implicitly • Each representation may serve one high-level goal Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 23 CH C/P/M 715, Taylor SP11 Visualization Goals • Debugging – Quality control of simulations, measurements • Exploration – Gaining new insights � hypotheses – Increasing scientific productivity – Making invisible visible • Presentation – Enhancing understanding of concepts and processes – Visual medium of communication Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 24 CH C/P/M 715, Taylor SP11 8

1/15/2014 Exploration Tasks • Identify and distinguish objects Specialized – Categorize objects • Compare values – Discover extrema (qualitative) – Look up metric information (quantitative) • Recognize pattern/structure – Identify clusters – Correlations between data sets – “What’s going on here?” General Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 25 CH C/P/M 715, Taylor SP11 Presentation Tasks • Effective presentation of significant features • Attempt to convince • Attract interest Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 26 CH C/P/M 715, Taylor SP11 Example: to Convince Tufte, The Visual Display of Quantitative Information, p. 41. • Visualization in the Sciences UNC- 01/16/2014 Characteristics and Goals 27 CH C/P/M 715, Taylor SP11 9